The first part of this dissertation studies genetic algorithms as a means of estimating the number of changepoints and their locations in a climatic time series. Such methods bypass classical subsegmentation algorithms, which sometimes yield suboptimal conclusions. Minimum description length techniques are introduced. These techniques require optimizing an objective function over all possible changepoint numbers and location times. Our general objective functions allow for correlated data, reference station aspects, and/or non-normal marginal distributions, all common features of climate time series. As an exhaustive evaluation of all changepoint configurations is not possible, the optimization is accomplished via a genetic algorithm that r...
Analog methods (AMs) are statistical downscaling methods often used for precipitation prediction in ...
Global warming is a well-known and well-studied phenomenon pertaining to a gradual increase of avera...
This paper develops trend estimation techniques for monthly maximum and minimum temperature time ser...
The first part of this dissertation studies genetic algorithms as a means of estimating the number o...
AbstractWe use genetic programming (GP), a variant of evolutionary computation, to build interpretab...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
The prerequisite of the homogenization of climatological time series is to find the points of time w...
Analog methods (AMs) allow for the prediction of local meteorological variables of interest(predicta...
Computational intelligence and other data mining techniques are used for characterizing regional and...
The United States Department of Agriculture classifies plant hardiness zones based on mean annual mi...
This dissertation develops a minimum description length (MDL) multiple changepoint detection procedu...
The Analogue Method (AM) aims at forecasting a local meteorological variable of interest (the predic...
To keep pace with future climate change, forest tree species are often predicted to need to shift th...
Weather systems use extremely complex combinations of mathematical tools for anal-ysis and forecasti...
BACKGROUND In recent years, the price drop in off-the-shelf computer systems has enabled small insti...
Analog methods (AMs) are statistical downscaling methods often used for precipitation prediction in ...
Global warming is a well-known and well-studied phenomenon pertaining to a gradual increase of avera...
This paper develops trend estimation techniques for monthly maximum and minimum temperature time ser...
The first part of this dissertation studies genetic algorithms as a means of estimating the number o...
AbstractWe use genetic programming (GP), a variant of evolutionary computation, to build interpretab...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
The prerequisite of the homogenization of climatological time series is to find the points of time w...
Analog methods (AMs) allow for the prediction of local meteorological variables of interest(predicta...
Computational intelligence and other data mining techniques are used for characterizing regional and...
The United States Department of Agriculture classifies plant hardiness zones based on mean annual mi...
This dissertation develops a minimum description length (MDL) multiple changepoint detection procedu...
The Analogue Method (AM) aims at forecasting a local meteorological variable of interest (the predic...
To keep pace with future climate change, forest tree species are often predicted to need to shift th...
Weather systems use extremely complex combinations of mathematical tools for anal-ysis and forecasti...
BACKGROUND In recent years, the price drop in off-the-shelf computer systems has enabled small insti...
Analog methods (AMs) are statistical downscaling methods often used for precipitation prediction in ...
Global warming is a well-known and well-studied phenomenon pertaining to a gradual increase of avera...
This paper develops trend estimation techniques for monthly maximum and minimum temperature time ser...